On a chromatogram obtained by a chromatographic analysis, such as a gas chromatography or liquid chromatography, a peak corresponding to a component contained in a sample appears. Normally, the position (time) where the peak appears depends on the kind of compound, while the size of the peak (i.e. its height or area) depends on the amount or concentration of the component corresponding to the peak. Therefore, in order to identify a component in a sample by using a chromatogram, it is important to accurately determine the position of the peak. Similarly, in order to comprehend the amount or concentration of a component in a sample, it is important to accurately determine the height or area of the peak. In any cases, to determine the position of a peak on a chromatogram as well as the height or area value of the peak, it is necessary to correctly detect a significant peak originating from a component based on the waveform of the chromatogram.
In many conventionally and commonly used techniques for detecting a peak on a chromatogram, the tangential inclination of the chromatogram waveform is used as the reference, as in the case of the method described in Non Patent Literature 1. However, such a method has the problem that it is difficult to correctly detect a peak if there is a change in the baseline (as shown in FIG. 5A) or if a considerable amount of noise is superposed (as shown in FIG. 5B). Needless to say, the influence of the baseline change or that of the noise can to some extent be removed by performing a pre-process before the peak detection, such as the baseline correction or the smoothing process for noise removal. However, such a process does not always produce a satisfactory effect.
The tangential inclination of the chromatogram waveform for determining a true peak depends on the width of the peak. Therefore, in order to correctly detect a peak, it is necessary to set the peak detection parameters (e.g. the threshold of the inclination used as the criterion for determination) for each sample. However, in the case of a metabolic analysis, a biomarker search or similar analysis in which a considerable number of samples need to be almost continuously analyzed, it is difficult to set the peak detection parameters for each sample, which means that it is difficult to equally improve the accuracy of the peak detection for a variety of samples.
As a peak detection method which is entirely different from the conventional method and one which can solve the aforementioned problems, a method which uses a ridge line in a wavelet coefficient space has been proposed (see Non Patent Literature 2; this method is hereinafter called the “wavelet ridge line detection method”). The wavelet ridge line detection method is hereinafter briefly described.
In the wavelet ridge line detection method, on raw spectrum data (profile spectrum data) obtained by a mass spectrometry, a continuous wavelet transform is directly performed. i.e. without performing the preprocessing for the baseline correction or noise removal. The wavelet coefficients are determined while a scale factor is varied. The scale factor is one of the two parameters used in transforming the mother wavelet into a wavelet function. It is a parameter for scaling the mother wavelet. In general, the wavelet coefficient relatively shows the extent to which the component of the wavelet function given under specific parameters (e.g. the scale factor) is contained in the original waveform of the signal. In the wavelet ridge line detection method, for each mass-to-charge ratio, the wavelet coefficient is calculated while the scale factor is changed. The calculated result is visualized in a three-dimensional coefficient space with the horizontal axis indicating the mass-to-charge ratio, the vertical axis indicating the scale factor, and the third axis orthogonal to both of the horizontal and vertical axes indicating the strength of the wavelet coefficient. In the visualized image, a characteristic ridge line which shows a local maximum is observed at the position corresponding to a true peak formed on the waveform of the original profile spectrum. This ridge line is utilized to detect the peak on the waveform of the profile spectrum.
The baseline change of the waveform of the profile spectrum over a narrow range of time can be regarded as an odd function. Therefore, by using an even function as the mother wavelet, the odd-function component due to the baseline change can be cancelled out, making it possible to correctly detect a peak without performing the baseline correction beforehand. Another characteristic of this method is that the peaks having various peak widths can be correctly detected by performing a comparative evaluation of the strengths of the wavelet coefficients obtained by using the wavelet functions having various widths produced by changing the scale factor.
The previously described processing, such as the calculation and three-dimensional visualization of the wavelet coefficient by the continuous wavelet transform as well as the display of the ridge line showing a plot of the maximum value of the wavelet coefficient, can be performed by using an existing software program, such as the one described in Non Patent Literature 3.